1. Field of the Invention
The herein claimed method relates to the field of diagnostic assessment of fine textures in biological systems for pathology assessment and disease diagnosis, and in material and structural evaluation in industry and in engineering research. More specifically, the invention employs a method for repeat measurement of k-values associated with the spatial organization of biologic tissue texture, with the MRI machine gradients turned off. This allows assessment of tissue texture on a time-scale on the order of a msec, whereby the problem of patient motion becomes negligible. The method enables in vivo assessment, towards diagnosis and monitoring, of disease and therapy-induced textural changes in tissue. Representative targets of the technique are: 1) for assessment of changes to trabecular architecture caused by bone disease, allowing assessment of bone health and fracture risk, 2) evaluation of fibrotic development in soft tissue diseases such as, for example, liver, lung, and heart disease, and 3) changes to fine structures in neurologic diseases, such as the various forms of dementia, or in cases of brain injury and downstream neuro-pathology as in, for example, Traumatic Brain Injury (TBI) and Chronic Traumatic Encephalopathy (CTE), or for characterization and monitoring of abnormal neurologic conditions such as autism and schizophrenia. Other pathology applications include assessment of vascular changes such as in in the vessel network surrounding tumors or associated with development of CVD (Cerebrovascular Disease), and of changes in mammary ducting in response to tumor growth. The invention also has applications in assessment of fine structures for a range of industrial purposes such as measurement of material properties in manufacturing or in geology to characterize various types of rock, as well as other uses for which measurement of fine structures/textures is needed.
2. Description of the Related Art
Though fine textural changes in tissue have long been recognized as the earliest markers in a wide range of diseases, robust clinical assessment of fine texture remains elusive, the main difficulty arising from blurring caused by subject motion over the time required for data acquisition.
Early and accurate diagnosis is key to successful disease management. Though clinical imaging provides much information on pathology, many of the tissue changes that occur as a result of disease onset and progression, or as a result of therapy, are on an extremely fine scale, often down to tens of microns. Changes in fine tissue texture have been recognized for many years by diagnosticians, including radiologists and pathologists as the earliest harbinger of a large range of diseases, but in vivo assessment and measurement of fine texture has remained outside the capabilities of current imaging technologies. For instance, differential diagnosis of obstructive lung disease relies on a textural presentation in the lung parenchyma, but the robustness of the Computed Tomography (CT) measure of early stage disease is limited. Trabecular bone microarchitecture, the determinant of fracture risk in aging bone, has also remained elusive due to image blurring from patient motion during Magnetic Resonance (MR) imaging scans. Post processing analysis of MR-images is sometimes used to try to differentiate surface textures in structures such as tumors and white matter. (DRABYCZ, S., et al.; “Image texture characterization using the discrete orthogonal S-transform”; Journal of Digital Imaging, Vol. 22, No 6, 2009. KHIDER, M., et al.; “Classification of trabecular bone texture from MRI and CT scan images by multi-resolution analysis”; 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2007.) But post processing analysis is limited in effect as it doesn't deal with the underlying problem that prevents high resolution acquisition of textural information, i.e. subject motion. (MACLAREN, J. et al.; “Measurement and correction of microscopic head motion during magnetic resonance imaging of the brain”, PLOS/ONE, Nov. 7, 2012. MACLARAN, J. et al.; “Prospective motion correction in brain imaging: a review; Magnetic Resonance in Medicine, Vol. 69, 2013.)
The main sources of motion affecting MR imaging are cardiac pulsatile motion, respiratory-induced motion and twitching. The first two are quasi-cyclic, the usual approach to which is gating at the slowest phase of motion. However, even with gating, there is sufficient variation between acquisitions to cause loss of spatial phase coherence at the high k-values of interest for texture measurements. This problem is exacerbated by the fact that motion may not be perfectly cyclic, and often originates from combined sources. Twitching is rapid, inducing random displacements, and hence it is not possible to maintain coherence at the high k-values of interest when measuring texture.
While Positron Emission Tomography (PET) provides valuable diagnostic information, it is not capable of resolution below about 5 mm and relies on the use of radioactive tracers for imaging as well as x-ray beams for positioning, raising dose concerns, especially if repeat scanning is needed. (BERRINGTON DE GONZALEZ, A. et al.; “Projected cancer risks from Computed Tomographic scans performed in the United States in 2007”; JAMA Internal Medicine, Vol. 169, No. 22, December 2009.) Further, PET imaging is extremely costly, requiring a nearby cyclotron. CT resolution down to 0.7 mm is possible in theory, though this is obtained at high radiation dose and is subject to reduction by patient motion over the few minute scan time. The non-negligible risk from the associated radiation dose makes CT problematic for longitudinal imaging and limits available resolution. Along with serious dose concerns, digital x-ray resolution is limited because the 2-dimensional image obtained is a composite of the absorption through the entire thickness of tissue presented to the beam. Current clinical diagnostics for the diseases that are the target of the method claimed herein are fraught with difficulties in obtaining sufficient in vivo resolution, or accuracy. In some cases, no definitive diagnostic exists currently. In other pathologies, particularly in breast and liver, diagnosis is dependent on biopsy, with its non-negligible risk of morbidity and even mortality, and which is prone to high read and sampling errors. (WELLER, C; “Cancer detection with MRI as effective as PET-CT scan but with zero radiation risks”; Medical Daily, Feb. 18, 2014.)
Bone health is compromised by aging, by bone cancer, as a side effect of cancer treatments, diabetes, rheumatoid arthritis, and as a result of inadequate nutrition, among other causes. Bone disease affects over ten million people annually in the US alone, adversely affecting their quality of life and reducing life expectancy. For assessment of bone health, the current diagnostic standard is Bone Mineral Density (BMD), as measured by the Dual Energy X-ray Absorptiometry (DEXA) projection technique. This modality yields an areal bone density integrating the attenuation from both cortical and trabecular bone, similar to the imaging mechanism of standard x-ray, but provides only limited information on trabecular architecture within the bone, which is the marker linked most closely to bone strength. (KANIS, J. AND GLUER, C.; “An update on the diagnosis and assessment of osteoporosis with densitometry”; Osteoporosis International, Vol. 11, issue 3, 2000. LEGRAND, E. et al.; “Trabecular bone microarchitecture, bone mineral density, and vertebral fractures in male osteoporosis”; JBMR, Vol. 15, issue 1, 2000.) BMD correlates only loosely with fracture risk. A post-processing technique, TBS (Trabecular Bone Score) attempts to correlate the pixel gray-level variations in the DEXA image, to yield information on bone microarchitecture. A comparison study determined that BMD at hip remains a better predictor of fracture. But, though TBS does not yield a detailed assessment of trabecular architecture. (BOUSSON, V., et al.; “Trabecular Bone Score (TBS): available knowledge, clinical relevance, and future prospects”; Osteoporosis International, Vol. 23, 2012. DEL RIO, et al.; “Is bone microarchitecture status of the spine assessed by TBS related to femoral neck fracture? A Spanish case-control study”: Osteoporosis International, Vol. 24, 2013.) TBS is a relatively new technique and is still being evaluated.
Measurement of bone microarchitecture, specifically trabecular spacing and trabecular element thickness, requires resolution on the order of tenths of a millimeter. MRI, ultrasound imaging, CT, and microCT have all been applied to this problem. In MRI, though high contrast between bone and marrow is readily obtained, resolution is limited by patient motion over the long time needed to acquire an image with sufficient resolution to characterize the trabecular network. The finer the texture size of this network, the greater the blurring from motion. An attempt to mitigate the effects of patient motion by looking only at the skeletal extremities, removed from the source of cardiac and respiratory motion sources, has been tried using both MRI and microCT. However, the correlation between bone microarchitecture in the extremities and that in central sites in not known. Further, a large data matrix, hence long acquisition time, is still required to obtain sufficient image information to determine trabecular spacing and element thickness. This long acquisition time results in varying levels of motion-induced blurring, depending on patient compliance—twitching is still a serious problem even when measuring extremities. A proposed MR-based technique, fineSA (JAMES, T., CHASE, D.; “Magnetic field gradient structure characteristic assessment using one dimensional (1D) spatial-frequency distribution analysis”; U.S. Pat. No. 7,932,720 B2; Apr. 26, 2011.), attempts to circumvent the problem of patient motion by acquiring a much smaller data matrix of successive, finely-sampled, one-dimensional, frequency-encoded acquisitions which are subsequently combined to reduce noise. Imaging in this case is reduced to one dimension, reducing the size of the data matrix acquired and, hence, the acquisition time. However, as the gradient encoded echoes, are very low Signal to Noise (SNR), noise averaging is required. Though some resolution advantage is gained by this method relative to 2 and 3-d imaging, the need to acquire many repeat spatially-encoded echoes over several response times (TRs) for signal averaging results in an acquisition time on the order of minutes—too long to provide motion immunity. Thus, resolution improvement obtainable by the technique is limited.
What is needed is an accurate, robust, non-invasive, in vivo measure of trabecular spacing and trabecular element thickness capable of assessing bones in the central skeleton, as these are the key markers for assessing bone health and predicting fracture risk. Until now, no clinical technique has been able to provide this capability.
Fibrotic diseases occur in response to a wide range of biological insults and injury in internal organs, the development of collagen fibers being the body's healing response. The more advanced a fibrotic disease, the higher the density of fibers in the diseased organ. Fibrotic pathology occurs in a large number of diseases, from lung and liver fibrosis, to cardiac and cystic fibrosis, pancreatic fibrosis, muscular dystrophy, bladder and heart diseases, and myelofibrosis, in which fibrotic structures replace bone marrow. Fibrotic development is attendant in several cancers, such as breast cancer. A different pathology development is seen in prostate cancer, where the disease destroys healthy organized fibrous tissue. In all cases, textural spacings highlighted in the tissue change in response to disease progression, as collagen fibers form along underlying tissue structures. In liver disease, the textural wavelength changes as the healthy tissue texture in the liver is replaced by a longer wavelength texture originating from the collagen “decoration” of the lobular structure in the organ. In other organs/diseases, textural change reflects the upset in healthy tissue with development of texture indicative of fibrotic intervention.
To span the range of disease progression in most fibrotic pathologies, evaluation of textural changes from fibrotic development requires resolution on the scale of tenths of a mm. One of the most prevalent of such pathologies, liver disease, is representative of the difficulty of assessing fibrotic structure. Currently, the gold standard for pathology assessment is tissue biopsy—a highly invasive and often painful procedure with a non-negligible morbidity—and mortality—risk (patients need to stay at the hospital for post-biopsy observation for hours to overnight), and one that is prone to sampling errors and large reading variation. (REGEV, A.; “Sampling error and intraobserver variation in liver biopsy in patients with chronic HCV infection”; American Journal of Gastroenterology; 97, 2002. BEDOSSA, P. et al.; “Sampling variability of liver fibrosis in chronic hepatitis C”; Hepatology, Vol. 38, issue 6, 2004. VAN THIEL, D. et al.; “Liver biopsy: Its safety and complications as seen at a liver transplant center”; Transplantation, May 1993.) Ultrasound, another modality often used to assess tissue damage in liver disease, is only able to provide adequate assessment in the later stages of the disease—it is used to diagnose cirrhosis. Magnetic Resonance-based Elastography (MRE), which has been under development for some time for use in assessment of liver disease, is not capable of early-stage assessment—the read errors are too large prior to significant fibrotic invasion (advanced disease). Further, this technique requires expensive additional hardware, the presence of a skilled technician, and takes as much as 20 minutes total set up and scanning time, making it a very costly procedure. The ability to image fibrotic texture directly by MR imaging is compromised both by patient motion over the time necessary to acquire data and by lack of contrast between the fibers and the surrounding tissue. Even acquisition during a single breath hold is severely compromised by cardiac pulsatile motion and noncompliance to breath hold, which results in significant motion at many organs, such as liver and lungs. And SNR is low enough that motion correction by combining reregistered MR-intensity profiles obtained from successive echoes is extremely problematic. Similarly, assessment of the amount of cardiac fibrosis in early stage disease using MRI is seriously hampered by cardiac pulsation over the time of the measurement. As motion is, unlike Gaussian noise, a non-linear effect, it can't be averaged out—there must be sufficient signal level to allow reregistration before averaging for electronic noise-reduction. A more sensitive (higher SNR), non-invasive technique, capable of assessing textural changes throughout the range of fibrotic development, from onset to advanced pathology, is needed to enable diagnosis and monitoring of therapy response.
Onset and progression of a large number of neurologic diseases are associated with changes in repetitive fine neuronal and vascular structures/textures. However, ability to assess such changes in the brain is only available post mortem. Currently, definitive diagnosis of Alzheimer's Disease (AD) is by post mortem histology of brain tissue. AD and other forms of dementia such as Dementia with Lewy Bodies, motor diseases such as Amyotrophic Lateral Sclerosis (ALS), Parkinson's disease, conditions precipitated by Traumatic Brain Injury (TBI) such as Chronic Traumatic Encephalopathy (CTE), as well as those caused by other pathologies or trauma, or conditions that involve damage to brain structures such as Multiple Sclerosis (MS), Cerebrovascular Disease (CVD), and other neurologic diseases, are often only diagnosable in advanced stages by behavioral and memory changes, precluding the ability for early stage intervention. Further, conditions such as epilepsy and autism have been associated with abnormal variations in fine neuronal structures, which, if clinically diagnosable, would allow targeted selection for testing therapy response.
Various in vivo diagnostic techniques are available for AD and other dementias, but none of them are definitive. These techniques range from written diagnostic tests, which are prone to large assessment errors, to PET imaging to assess amyloid plaque density or glucose metabolism (FDG PET). As discussed previously, PET imaging is extremely expensive, cannot provide high resolution, and relies on use of radioisotopes and positioning x-ray beams, complicating approval for longitudinal use due to dose concerns. Further, neither amyloid imaging nor FDG PET has been shown to provide a definitive indication of AD. (MOGHBEL, M. et al. “Amyloid Beta imaging with PET in Alzheimer's disease: is it feasible with current radiotracers and technologies?”; Eur. J. Nucl. Med. Mol. Imaging.)
Use of CSF biomarkers for dementia diagnosis is painful and highly invasive and cannot differentiate signal levels by anatomic position in the brain, as is possible with imaging biomarkers. As various forms of dementia are found to have different spatial/temporal progression through the brain, this is a serious drawback to use of liquid biopsy. Another disease associated with various forms of dementia is CVD (Cerebrovascular Disease), which induces cognitive impairment as a result of reduced blood flow through blocked vessels leading to brain tissue. Something capable of high-resolution assessment of pathology-induced changes in micro-vessels is needed here.
Tissue shrinkage due to atrophy in many forms of dementia including AD is measurable with careful registration of longitudinally-acquired data in MRI, but the disease is advanced by the time this shrinkage is measurable. Early stages of disease are indicated in post mortem histology by degradation in the columnar ordering of cortical neurons, the normal spacing for these columns being on the order of 100 microns in most cortical regions. (CHANCE, S. et al.; “Microanatomical correlates of cognitive ability and decline: normal aging, MCI, and Alzheimer's disease”; Cerebral Cortex, August 2011. E. DI ROSA et al.; “Axon bundle spacing in the anterior cingulate cortex of the human brain”; Journal of Clinical Neuroscience, 15, 2008.) This textural size, and the fact that the cortex is extremely thin, makes speed of acquisition paramount, as even tiny patient motion will make data collection impossible. Assessment of textural changes on the order of tens of microns microns is extremely problematic in vivo, but would, if possible, enable targeting a range of fine textural changes in neuronal disease diagnosis and monitoring, and would play an important role in therapy development.
Another possible neurologic application for the claimed method is to, in vivo, determine the boundaries of the various control regions of the cerebral cortex or the different Brodmann's areas of which these are comprised. Such ability would greatly aid data interpretation in brain function studies, such as those performed using, for example, FMRI (Functional Magnetic Resonance Imaging).
The three classes of diseases listed above, bone disease, fibrotic diseases, and neurologic diseases are not an all-inclusive list. Other disease states in which pathology-induced changes of fine structures occur, for instance angiogenic growth of vasculature surrounding a tumor, or fibrotic development and changes in vasculature and mammary gland ducting in response to breast tumor development, also are pathologies wherein the ability to resolve fine tissue textures would enable early detection of disease, and monitoring of response to therapy.
The ability to measure changes in fine textures would be of great value for disease diagnosis. Non-invasive techniques that do not rely on use of ionizing radiation or radioactive tracers allow the most leeway for early diagnosis and repeat measurement to monitor disease progression and response to therapy. Magnetic Resonance Imaging (MRI), which provides tunable tissue contrast, is just such a non-invasive technique, with no radiation dose concerns. However, in order to circumvent the problem of signal degradation due to patient motion, data must be taken on a time scale not previously possible.